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Biplots in Reduced‐Rank Regression

Biplots in Reduced‐Rank Regression Regression problems with a number of related response variables are typically analyzed by separate multiple regressions. This paper shows how these regressions can be visualized jointly in a biplot based on reduced‐rank regression. Reduced‐rank regression combines multiple regression and principal components analysis and can therefore be carried out with standard statistical packages. The proposed biplot highlights the major aspects of the regressions by displaying the least‐squares approximation of fitted values, regression coefficients and associated t‐ratios. The utility and interpretation of the reduced‐rank regression biplot is demonstrated with an example using public health data that were previously analyzed by separate multiple regressions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biometrical Journal Wiley

Biplots in Reduced‐Rank Regression

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References (39)

Publisher
Wiley
Copyright
Copyright © 1994 WILEY‐VCH Verlag GmbH & Co. KGaA
ISSN
0323-3847
eISSN
1521-4036
DOI
10.1002/bimj.4710360812
Publisher site
See Article on Publisher Site

Abstract

Regression problems with a number of related response variables are typically analyzed by separate multiple regressions. This paper shows how these regressions can be visualized jointly in a biplot based on reduced‐rank regression. Reduced‐rank regression combines multiple regression and principal components analysis and can therefore be carried out with standard statistical packages. The proposed biplot highlights the major aspects of the regressions by displaying the least‐squares approximation of fitted values, regression coefficients and associated t‐ratios. The utility and interpretation of the reduced‐rank regression biplot is demonstrated with an example using public health data that were previously analyzed by separate multiple regressions.

Journal

Biometrical JournalWiley

Published: Jan 1, 1994

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